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Senior Developer, AI Evaluation & Cloud Infrastructure | Just Horizons Alliance

Join us to build the technical foundation for AI accountability.

The Role

Just Horizons Alliance is an 18-year-old applied research lab focused on ethics and technology. Our current focus is the AI Ethics Index, a measurement framework for evaluating AI systems on ethics, safety, and societal impact.

We need a senior engineer to own the technical infrastructure end-to-end: learn what exists, close critical gaps, and build something that lasts.

The evaluation methodology is validated and in use. We're now at the stage where the systems need to mature alongside the research. This is the first dedicated infrastructure hire for this work, and you'll shape how it scales.

What You'll Do

Months 1–3: Learn the System

Map the current architecture with Sophia Zitman (AIEI Team Lead). Understand the evaluation methodology, the data flows, and the infrastructure that supports them. Identify what needs to evolve for multi-domain benchmarking—reproducibility, security posture, test coverage, deployment pipeline. Begin implementing the highest-priority improvements.

Months 4–6: Build for Scale

Architect the infrastructure to support the next phase of the Index. CI/CD that maintains stability as the system grows. IAM and secret management built for a production environment. Experiment tracking that makes every evaluation run auditable. Documentation that enables the research team to work independently.

Months 7–12: Expand

Multi-domain benchmarking across education, healthcare, finance, and other sectors. Reproducibility standards that meet external scientific scrutiny. A system the research team can extend without engineering support for every change. At this point, the infrastructure should be stable enough that you're focused on capability, not maintenance.

Why This Role Is Difficult

This is infrastructure for a scientific standard, not a product feature.

Correctness and delivery both matter. A bug in the evaluation engine doesn't break a feature, instead it invalidates a measurement. A flawed pipeline doesn't slow things down, it compromises the credibility of the research. At the same time, methodology that never runs in production has no impact. The role requires both rigor and momentum.

You're translating between disciplines. Your stakeholders are researchers, ethicists, and governance specialists. You'll need to take concepts like \"operationalizing an ethical construct\" and turn them into data models and pipelines. This is a translation problem as much as an engineering problem.

The work is novel. There's no existing system to reference. The AI Ethics Index is defining what rigorous AI evaluation looks like. You'll be making architectural decisions in areas where best practices don't yet exist.

You'll have full ownership. This is not a role where you're executing someone else's technical vision. You're setting the direction. That means autonomy, but it also means accountability.

You're probably the right person if

You've built evaluation systems or data pipelines that other people depended on for correctness, not just uptime

You're comfortable with GCP and have deployed containerized workloads in a real production context

You've worked with LLM APIs and understand their reliability and reproducibility characteristics

You can read a paper about measurement methodology and turn it into a working data structure

You build for durability. Your code is still running 18 months later because you thought about the next person

You've worked somewhere between 5 and 50 people and you're comfortable being the person who figures things out without a playbook

You find working on AI ethics infrastructure more interesting than building another e-commerce checkout flow

You're probably not the right fit if

Enterprise environments make up most of your experience. This is not a large-team context

You need clearly defined requirements before you can start. The requirements here evolve through conversation with ethicists

You're based on the West Coast US or expect West Coast US working hours

You mainly build user-facing APIs and features — this is systems and infrastructure work

You're looking for a high-growth startup where shipping speed is everything. This is a scientific organization. Correctness is everything.

Hard Skills

These are the technical capabilities you need going in — or need to be able to build up fast using an AI coding agent. We're not looking for someone who ticks every box. We're looking for someone who closes gaps quickly and knows how to learn.

• Python — strong enough to design systems architecture and reason about failure modes, even if you work with AI assistance for implementation details
• Google Cloud Platform — specifically Cloud Run, IAM design, secret management, and containerized workload deployment in a real production context
• API and model documentation — able to read, write, and navigate API specs and model documentation fluently; you know how to figure out how a system behaves from its documentation without needing someone to walk you through it
• Structured step-by-step reasoning — when you hit a complex problem, you decompose it immediately and visibly into logical steps; you don't disappear into your head and come back with an answer, you think out loud and in sequence, which makes collaboration with the ethics and research team possible
• LLM API integration — understanding the reliability, reproducibility, and failure characteristics of external model endpoints
• Data pipeline architecture — building evaluation or measurement systems where correctness is non-negotiable, not just data-moving
• Experiment tracking and reproducibility standards — always looking to improve the evaluation pipeline; you understand what needs to be tracked, why reproducibility matters scientifically, and you find the right approach for the context without being dogmatic about tooling
• Statistical reliability concepts — enough to understand what inter-rater reliability means for evaluation output and why reproducibility matters scientifically

What you get

The role: You'll work directly with Sophia Zitman (AIEI Team Lead) as the technical backbone of the AI Ethics Index. Full engineering ownership of the evaluation engine.

The comp: Base salary $110,000.

The team: Small, split between ethicists and engineers. You will interview with Janet Kang (Executive Director) and Sophia Zitman (AIEI Team Lead).

The environment: Boston-based non-profit (501(c)(3)). East Coast US or Western Europe time zones. Collaborative but autonomous — Sophia won't micromanage, but she will hold you to a high standard of systems thinking.

The upside: You'll have built the technical foundation of what may become the globally referenced standard for AI system evaluation. That's a meaningful line on any CV — and a genuinely hard thing to have done.

Role Overview

We are seeking a highly experienced Senior AI Architect to lead the design and implementation of enterprise-scale Agentic AI systems and multi-agent orchestration platforms. This role requires deep expertise in LLM-based architectures, distributed systems, and cloud-native infrastructure.

As a technical authority, you will guide enterprise clients through their Agentic AI transformation, from evaluating AI frameworks and communication protocols to deploying scalable, production-ready AI automation solutions.

You will work at the forefront of GenAI platform engineering, designing architectures that power intelligent automation, enterprise knowledge systems, and AI-driven workflows.

Key Responsibilities

Agentic AI Architecture & Design

• Design and implement end-to-end multi-agent orchestration systems for enterprise automation and decision intelligence.
• Define agent design patterns, including agent roles, delegation frameworks, task decomposition, and orchestration strategies.
• Architect scalable agent ecosystems with lifecycle management, monitoring, fallback mechanisms, and human-in-the-loop capabilities.
• Evaluate and implement inter-agent communication protocols such as MCP, A2A, REST, gRPC, JSON-RPC, and event-driven messaging.

GenAI & Foundation Model Integration

• Select and integrate LLMs and foundation models (OpenAI, Anthropic, Gemini, Mistral, Llama, etc.) based on task requirements.
• Develop advanced prompt engineering and context management strategies, including:
• Few-shot prompting
• Chain-of-thought reasoning
• Retrieval-Augmented Generation (RAG)
• Structured output pipelines
• Implement tool and function calling patterns enabling agents to interact with enterprise APIs, databases, and services.
• Optimize context window management, token budgets, and dynamic context injection for scalable production systems.

State Management & Agent Memory

• Architect stateful AI systems with short-term, long-term, and episodic memory layers.
• Implement persistence strategies using:
• Vector databases
• Key-value stores
• Graph databases
• Relational systems
• Design auditable and idempotent execution patterns suitable for enterprise governance and compliance requirements.

Microservices & Platform Engineering

• Build AI platforms using loosely coupled microservices with scalable APIs and observability built in.
• Deploy AI systems using container orchestration platforms such as Kubernetes (EKS, AKS, or GKE).
• Establish CI/CD pipelines for AI workloads including model versioning, prompt versioning, and deployment strategies.
• Promote Infrastructure-as-Code (IaC) using tools like Terraform and GitOps deployment practices.

Enterprise Client Engagement

• Partner with enterprise stakeholders to assess AI readiness and automation opportunities.
• Translate complex business requirements into scalable AI system architectures.
• Provide guidance on build vs. buy decisions for AI frameworks and vendor tools.
• Produce architecture documentation, reference designs, and implementation playbooks.

Required Qualifications

• 8+ years of experience in software engineering or platform architecture.
• 3+ years of experience designing AI/ML systems or GenAI platforms.
• Hands-on experience building multi-agent or agentic AI orchestration systems in production.
• Strong experience with agent frameworks such as:
• LangChain
• LangGraph
• AutoGen
• CrewAI
• Semantic Kernel
• Expertise integrating LLMs, embeddings, tool/function calling, and RAG pipelines.
• Deep knowledge of microservices architecture, distributed systems, and API design.
• Experience with container orchestration (Kubernetes preferred) and cloud platforms such as GCP, AWS, or Azure.
• Strong programming skills in Python, with additional experience in TypeScript, Go, or Java preferred.

Preferred Qualifications

• Experience working with enterprise clients or consulting environments.
• Knowledge of AI governance, responsible AI, and compliance frameworks.
• Familiarity with model fine-tuning, RLHF, or adapter-based model customization.
• Experience with AI observability tools such as LangSmith, Arize AI, or OpenTelemetry.
• Experience working with vector databases (Pinecone, Weaviate, Qdrant, pgvector).
• Contributions to open-source AI or agentic system projects.

At Rite-Hite, your work makes an impact. As the global leader in loading dock and door equipment, we design and deliver solutions that keep our customers safe, secure, and productive. Here, you'll find innovation, stability, and the chance to grow your career as part of a team that's always looking ahead.

ESSENTIAL DUTIES AND RESPONSIBILITIES

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.

• Design and build AI-powered applications using Large Language Models (LLMs) for enterprise use cases.
• Develop Retrieval-Augmented Generation (RAG) solutions using structured and unstructured enterprise data such as documents, manuals, tickets, ERP data, and knowledge bases.
• Build and orchestrate AI agents that can reason, plan, and interact with tools, APIs, and workflows.
• Implement guardrails for AI systems including prompt safety, data protection, hallucination mitigation, access control, and output validation.
• Work with multimodal AI models including text, image, and video use cases such as video analysis, summarization, and optimization.
• Integrate AI solutions with existing enterprise systems such as Salesforce, ERP platforms, data lakes, APIs, and internal applications.
• Partner with security and compliance teams to ensure responsible AI usage, data privacy, and governance.
• Prototype quickly, then harden solutions for production with monitoring, logging, evaluation, and performance optimization.
• Mentor and upskill existing developers on AI concepts, patterns, and best practices.

Required Skills & Experience

• 5+ year of full stack development experience.
• Strong software engineering background with experience building production-grade applications.
• Hands-on experience with modern LLM platforms such as OpenAI, Azure OpenAI, Anthropic, or similar.
• Practical experience building RAG pipelines using vector databases and embedding models.
• Experience with prompt engineering, prompt versioning, and evaluation techniques.
• Solid Python experience for AI development.
• Experience integrating AI services with REST APIs, microservices, and cloud-native architectures.
• Familiarity with cloud platforms such as AWS or Azure, including deployment, scaling, and security concepts.
• Understanding of data formats such as JSON, XML, and document-based data.
• Ability to translate business problems into AI-driven technical solutions.

Preferred Qualifications

• Experience with vector databases such as Pinecone, FAISS, Weaviate, or similar.
• Familiarity with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent orchestration tools.
• Experience implementing AI safety controls, policy enforcement, and evaluation frameworks.
• Exposure to video or image models and multimodal AI use cases.
• Experience working in enterprise environments with security, compliance, and change management considerations.
• Prior experience mentoring or leading developers in new technical domains.

What We Offer

At Rite-Hite, we take care of our people - because when you're supported, you can do your best work. Our benefits are designed to support your health, your future and your life outside of work:

• Health & Well-being: Comprehensive medical, dental, and vision coverage, plus life and disability insurance. A robust well-being program with an opportunity to receive an extra day off and more.

• Financial Security: A strong retirement savings program with 401(k), company match, and profit sharing.

• Time for You: Paid holidays, vacation time, and personal/sick days each year.

Join us and build a career where you're supported - at work and beyond.

Rite-Hite is proud to be an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under federal, state, or local law.In accordance with VEVRAA, we are committed to providing equal employment opportunities for protected veterans.We are also committed to maintaining a drug-free workplace for the safety of our employees and customers.

About Wakefern

Wakefern Food Corp. is the largest retailer-owned cooperative in the United States and supports its co-operative members' retail operations, trading under the ShopRite®, Price Rite®, The Fresh Grocer®, Dearborn Markets®, and Gourmet Garage® banners.

Employing an innovative approach to wholesale business services, Wakefern focuses on helping the independent retailer compete in a big business world. Providing the tools entrepreneurs need to stay a step ahead of the competition, Wakefern’s co-operative members benefit from the company’s extensive portfolio of services, including innovative technology, private label development, and best-in-class procurement practices.

The ideal candidate will have a strong background in designing, developing, and implementing complex projects, with focus on automating data processes and driving efficiency within the organization. This role requires a close collaboration with application developers, data engineers, data analysts, data scientists to ensure seamless data integration and automation across various platforms. The Data Integration & AI Engineer is responsible for identifying opportunities to automate repetitive data processes, reduce manual intervention, and improve overall data accessibility.

Essential Functions

• Participate in the development life cycle (requirements definition, project approval, design, development, and implementation) and maintenance of the systems.
• Implement and enforce data quality and governance standards to ensure the accuracy and consistency.
• Provide input for project plans and timelines to align with business objectives.
• Monitor project progress, identify risks, and implement mitigation strategies.
• Work with cross-functional teams and ensure effective communication and collaboration.
• Provide regular updates to the management team.
• Follow the standards and procedures according to Architecture Review Board best practices, revising standards and procedures as requirements change and technological advancements are incorporated into the >tech_ structure.
• Communicates and promotes the code of ethics and business conduct.
• Ensures completion of required company compliance training programs.
• Is trained – either through formal education or through experience – in software / hardware technologies and development methodologies.
• Stays current through personal development and professional and industry organizations.

Responsibilities

• Design, build, and maintain automated data pipelines and ETL processes to ensure scalability, efficiency, and reliability across data operations.
• Develop and implement robust data integration solutions to streamline data flow between diverse systems and databases.
• Continuously optimize data workflows and automation processes to enhance performance, scalability, and maintainability.
• Design and develop end-to-end data solutions utilizing modern technologies, including scripting languages, databases, APIs, and cloud platforms.
• Ensure data solutions and data sources meet quality, security, and compliance standards.
• Monitor and troubleshoot automation workflows, proactively identifying and resolving issues to minimize downtime.
• Provide technical training, documentation, and ongoing support to end users of data automation systems.
• Prepare and maintain comprehensive technical documentation, including solution designs, specifications, and operational procedures.

Qualifications

• A bachelor's degree or higher in computer science, information systems, or a related field.
• Hands-on experience with cloud data platforms (e.g., GCP, Azure, etc.)
• Strong knowledge and skills in data automation technologies, such as Python, SQL, ETL/ELT tools, Kafka, APIs, cloud data pipelines, etc.
• Experience in GCP BigQuery, Dataflow, Pub/Sub, and Cloud storage.
• Experience with workflow orchestration tools such as Cloud Composer or Airflow
• Proficiency in iPaaS (Integration Platform as a Service) platforms, such as Boomi, SAP BTP, etc.
• Develop and manage data integrations for AI agents, connecting them to internal and external APIs, databases, and knowledge sources to expand their capabilities.
• Build and maintain scalable Retrieval-Augmented Generation (RAG) pipelines, including the curation and indexing of knowledge bases in vector databases (e.g., Pinecone, Vertex AI Vector Search).
• Leverage cloud-based AI/ML platforms (e.g., Vertex AI, Azure ML) to build, train, and deploy machine learning models on a scale.
• Establish and enforce data quality and governance standards for AI/ML datasets, ensuring the accuracy, completeness, and integrity of data used for model training and validation.
• Collaborate closely with data scientists and machine learning engineers to understand data requirements and deliver optimized data solutions that support the entire machine learning lifecycle.
• Hands-on experience with IBM DataStage and Alteryx is a plus.
• Strong understanding of database design principles, including normalization, indexing, partitioning, and query optimization.
• Ability to design and maintain efficient, scalable, and well-structured database schemas to support both analytical and transactional workloads,
• Familiarity with BI visualization tools such as MicroStrategy, Power BI, Looker, or similar.
• Familiarity with data modeling tools.
• Familiarity with DevOps practices for data (CI/CD pipelines)
• Proficiency in project management software (e.g., JIRA, Clarizen, etc.)
• Familiarity with DevOps practices for data (CI/CD pipelines)
• Strong knowledge and skills in data management, data quality, and data governance.
• Strong communication, collaboration, and problem-solving skills.
• Ability to work on multiple projects and prioritize tasks effectively.
• Ability to work independently and in a team environment.
• Ability to learn new technologies and tools quickly.
• The ability to handle stressful situations.
• Highly developed business acuity and acumen.
• Strong critical thinking and decision-making skills.

Working Conditions & Physical Demands

This position requires in-person office presence at least 4x a week.

Compensation and Benefits

The salary range for this position is $75,868 - $150,644. Placement in the range depends on several factors, including experience, skills, education, geography, and budget considerations.

Wakefern is proud to offer a comprehensive benefits package designed to support the health, well-being, and professional development of our Associates. Benefits include medical, dental, and vision coverage, life and disability insurance, a 401(k) retirement plan with company match & annual company contribution, paid time off, holidays, and parental leave.

Associates also enjoy access to wellness and family support programs, fitness reimbursement, educational and training opportunities through our corporate university, and a collaborative, team-oriented work environment. Many of these benefits are fully or partially funded by the company, with some subject to eligibility requirements

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

As a Staff Software Engineer, you are a senior individual contributor who leads the design and delivery of significant platform features and raises the bar for engineering quality across the team. You'll work handson in code-designing APIs and data flows, building services in Python/FastAPI and React frontends, and guiding solutions from idea to production. You'll mentor engineers, influence architecture and standards within and adjacent to your team, and partner closely with product and design to achieve clear, measurable outcomes. This role blends deep implementation work with pragmatic technical leadership by example.

Essential Duties and Responsibilities

• Lead technical design for platform features and services, breaking ambiguous requirements into clear, incremental designs and stories for your team and adjacent partners.

• Implement backend services in Python/FastAPI and React frontends end-to-end, owning a continuous stream of stories from idea to production.

• Define and use clear API contracts and data flows between services and UIs, creating patterns and templates others can follow.

• Champion high-quality engineering practices, including code reviews, documentation, and maintainable, testable designs.

• Develop and improve automated testing (unit, integration, endtoend) and integrate these into everyday development and CI.

• Improve CI/CD pipelines and release workflows for your team so the team can ship small, safe changes frequently and confidently.

• Own the operational lifecycle of the features and services you build, including monitoring, observability, on-call participation, and incident follow-up.

• Design and implement secure-by-default solutions, including robust authentication/authorization, input validation, and safe handling of sensitive data.

• Identify and address reliability and performance risks early, proposing concrete technical improvements and sequencing them into the roadmap.

• Mentor and unblock engineers through pairing, design discussions, and clear feedback; influence without formal authority.

• Partners with product/design to shape requirements into incremental deliverables; escalates tradeoff decisions; proposes sequencing that optimizes value/risk.

The time spent on each responsibility reflects an estimate and is subject to change dependent on business needs.

Supervisory Responsibilities

No

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field; equivalent work experience is acceptable.

• 7+ years of experience in software engineering.

• Strong proficiency with Python and modern web backends (FastAPI, Flask, Django, or similar) and solid understanding of HTTP, API design, and data modeling.

• Significant experience with React (or a comparable SPA framework) and building production frontends that talk to backend APIs.

• Demonstrated ability to own features end-to-end in a small team: from shaping requirements through design, implementation, testing, deployment, and support.

• Experience designing and working with distributed systems or multi-service architectures (e.g., service boundaries, async jobs, integration patterns).

• Solid understanding of observability and operations for production systems (metrics, logs, traces, dashboards, alerting, incident response).

• Strong understanding of security fundamentals (authentication, authorization, secure data handling) and how they apply to web services and UIs.

• Deep familiarity with automated testing and CI/CD, and a track record of improving engineering workflows and quality.

• Excellent communication and collaboration skills; comfortable working closely with product, design, and other stakeholders.

• Proven ability to provide technical leadership in a hands-on way: unblocking others, making clear decisions, and raising the bar through code and reviews.

Bonus Qualifications

• Experience in early-stage or small platform teams where engineers wear multiple hats and balance shipping with building foundations.

• Experience with Azure and containerized deployments (or similar cloud-native environments).

• Experience building platforms (developer platforms, data platforms, or similar) that serve multiple product teams.

• Exposure to AI/ML or data-intensive applications (e.g., integrating with model inference APIs, data pipelines, or analytical data stores).

The base salary range for this position is$180,000 - $200,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

#LI-SS2 #LI-Remote

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime.

This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment.

The ideal candidate combines:

* Strong security engineering and cloud architecture experience

* Deep, current familiarity with modern AI/LLM tooling and practices

* Familiar and can cover basic coding within the AI tooling space (python, others)

* The ability to communicate clearly with senior leadership and influence enterprise-wide strategy

Essential Duties and Responsibilities

Secure AI / ML platforms and workloads

* Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications.

* Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads.

* Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation.

* Partner with data science and MLOps teams to harden:

• Data ingestion and labeling
• Training and fine-tuning pipelines
• Model registries and deployment workflows
• Inference APIs, agents, and integrations

* Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture.

AI use case intake & governance

* Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization.

* Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards.

* Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle.

* Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams.

* Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies.

Monitoring, detection & assurance

* Establish and maintain monitoring and detection for AI-specific threats, such as:

• Prompt injection and jailbreak attempts
• Data exfiltration and sensitive data exposure
• Misuse or abuse of AI tools and agents
• Anomalous model or pipeline behavior

* Integrate AI/ML systems with existing logging, SIEM, and incident response processes.

* Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification.

Strategy, leadership & enablement

* Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk.

* Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments.

* Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress.

* Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems.

Qualifications Expected for Position

• 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems.
• 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems.
• Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries.
• Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring.
• Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred.
• Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption.
• Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership.

Preferred Qualifications:

* Practical experience securing LLM- and genAI-based systems, such as:

• RAG architectures backed by internal data
• AI assistants, copilots, or agents integrated with enterprise tools
• Fine-tuned models and model hosting platforms

* Experience with AI IDE tools

• cursor, windsurfer, others
• Knows the security problems and has practical solutions that balances innovation with innovation.

* Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools).

* Experience with:

• Security for data pipelines, feature stores, and model registries
• Detection engineering or SIEM tuning for AI-related events
• Red-teaming or adversarial testing of AI systems

* Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks).

* Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports.

* Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus.

* Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape.

* High level of integrity and ethical conduct.

This role is a fit if you:

* Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects.

* Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems.

* Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation.

* Can move fluidly between deep technical discussions and concise, executive-level explanations.

This role is not a fit if you:

* Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work.

* Do not actively engage with current AI/LLM tooling, research, and emerging practices.

* "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?"

* "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?"

* "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?"

The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

Essential Duties and Responsibilities

• Work closely with business stakeholders toidentifyautomation opportunities.
• Lead the technical set up and integration ofconversational AI platform & agent development studiowithin the enterprise environment.- copilot agents preferred, deploying across enterprise not for personal use.
• Analyze business processes, data flows, and system architectures to support AI solution design.
• Support configuration and deployment of AI-powered agents,applications,and workflows.
• Design,build,and customize AI agents to automate workflows and improve productivity.
• Utilizedata platforms such asMicrosoft Fabric, Snowflake, Databricks, AWSfor data orchestration, governance, and compliance.
• Ensure seamless interoperabilityof agentsacrossMicrosoft and other enterprise applications asrequired.
• Evaluateand implement secure API integrationswith enterprise systems using APIsandconnectors to enable data exchange and workflow automation.
• Apply best practices for data security, identity management, and compliance with organizational and regulatory standards.
• Apply analytical judgment to assess feasibility, scalability, data readiness, and risks of AI use cases.
• Collaborate withcybersecurityand product teams to build robust AI solutions
• Test new AI agent enhancements, integrations, and fixes prior to release to ensure quality and expected behavior.
• Track and analyze performance metrics, including response quality, speed, reliability, andcost-effectivenessof AI agents and automated workflows.
• ContinuouslyoptimizeAI solutions based on performance data, user feedback, and evolving business needs.
• Document requirements, solution designs, architecture diagrams, and integration approaches in a clear and concise manner.
• Contribute to internal standards, reusable patterns, and best practices for AI agent and automation development.
• Support knowledge sharing and enablement across technical and business teams.

Qualifications Expected for Position

• Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related fieldor equivalent combination of education and relevant professional experience.
• Advanced certifications or coursework in cloud platforms, data engineering, or AI/ML preferred.
• 3+years of experience in solution architecture, systems integration, automation engineering, or applied AI roles.
• 1+ year demonstrated ability to design, build, and deployAI-poweredagents, workflows, or conversational applications.
• Proven experience working directly with business stakeholders to translate operational needs into scalable technical solutions.
• Hands-on experience implementing enterprise automation or conversational AI solutions across multiple departments or use cases.
• Experienceoperatingin regulated orsecurity-consciousenvironments, supporting compliance and governance requirements.
• Strong experience designing and implementing enterprise system integrations using APIs, connectors, and automation frameworks.
• Experience working with modern data platforms (e.g.,Microsoft Fabric, Snowflake, Databricks, AWS) to support data orchestration, access control, and compliance.
• Solid understanding of identity management, access controls, and data security best practices.
• Ability to assess AI solution feasibility, including data readiness, scalability, performance, and cost considerations.
• Strong analytical andproblem-solvingskills with the ability to apply sound judgment to ambiguous or emerging AI use cases.
• Excellent written and verbal communication skills, with the ability to explain technical concepts to nontechnical audiences.

The base salary range for this position is$130,000 - $140,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Job Title: Sr AI Platform Engineer- AI Platform Engineer (Guardrails, Observability & Evaluation Infrastructure)

Location, Charlotte, NC, USA (3 days onsite)

Role Overview

AI Platform Engineer to design and build the foundational components that power enterprise scale GenAI applications. This includes data guardrails, model safety tooling, observability pipelines, evaluation harnesses, and standardized logging/monitoring frameworks. This role is critical for enabling safe, reliable, and compliant AI development across multiple use cases, teams, and business units. Idea is to create the common platform services that AI team will build upon.

Key Responsibilities

1. Guardrails, Safety & Governance

• Design and implement data guardrail frameworks (pre processing, redaction, PII/PHI filtering, DLP integration, prompt defenses).

• Build "Model Armor" components such as:

o Input validation & sanitization

o Prompt injection defenses

o Harmful content detection & policy enforcement

o Output filtering, fact checking, grounding checks

• Integrate safety tooling (policy engines, classifiers, DLP APIs, safety models).

• Collaborate with Security, Compliance, and Data Privacy teams to ensure frameworks meet enterprise governance requirements.

2. Observability Frameworks

• Build and maintain observability pipelines using tools like Arize AI (tracing, quality metrics, dataset drift/hallucination tracking, embedding monitoring).

• Define and enforce platform wide standards for:

o Tracing LLM calls

o Token usage and cost monitoring

o Latency and reliability metrics

o Prompt/model version tracking

• Provide reusable SDKs or middleware for engineering teams to adopt observability with minimal friction.

3. Logging, Monitoring & Telemetry

• Design standardized LLM-specific logging schemas, including:

o Inputs/outputs

o Model metadata

o Retrieval metadata

o Safety flags

o User context and attribution

• Build monitoring dashboards for performance, cost, anomalies, errors, and safety events.

• Implement alerting and SLOs/SLIs for LLM inference systems.

4. Evaluation Infrastructure

• Architect and maintain evaluation harnesses for GenAI systems, including:

o RAG evaluation (faithfulness, relevance, hallucination risk)

o Summarization/QA evaluation

o Human-in-the-loop review workflows

o Automated eval pipelines integrated into CI/CD

• Support frameworks such as RAGAS, G Eval, rubric scoring, pairwise comparisons, and test case generation.

• Build reusable tooling for teams to write, run, and track model evaluations.

5. Platform Engineering & Reusable Components

• Develop shared libraries, APIs, and services for:

o Prompt management/versioning

o Embedding pipelines and model wrappers

o Retrieval adapters

o Common data loaders and document preprocessing

o Tool/function schemas

• Drive consistency across teams with standards, reference architectures, and best practices.

• Review system designs across use cases to ensure alignment to platform patterns.

6. Collaboration & Enablement

• Partner with AI engineers, product teams, and data scientists to understand cross cutting needs and convert them into reusable platform features.

• Create documentation, onboarding guides, examples, and developer tooling.

• Provide internal training (brown bags, workshops) on guardrails, observability, and evaluation frameworks.

Required Qualifications

Technical Skills

• 5–10+ years software engineering or ML infrastructure experience.

• Strong Python engineering fundamentals (FastAPI, async, typing/Pydantic, testing).

• Experience with model safety/guardrails approaches (prompt injection defense, PII redaction, toxicity filters, policy enforcement).

• Hands on with Arize AI, LangSmith, or similar LLM observability platforms.

• Experience creating evaluation frameworks using RAGAS, G Eval, or custom rubric systems.

• Strong familiarity with vector databases (Pinecone, Weaviate, Milvus), embeddings, and retrieval pipelines.

• Solid understanding of LLM architectures, tokenization, embeddings, context limits, and RAG patterns.

• Experience in cloud (GCP preferred), Kubernetes/GKE, containers, and CI/CD.

• Strong understanding of security, governance, DLP, data privacy, RBAC, and enterprise compliance requirements.

Soft Skills

• Strong documentation and communication skills.

• Ability to influence engineering teams and standardize best practices.

• Comfortable working across multiple stakeholders—platform, security, ML engineering, product.

Nice to Have

• Experience with LangChain/LangGraph or LlamaIndex orchestrations.

• Experience with , Rebuff, Protect AI, or similar LLM security tooling.

• Experience with GCP Vertex AI pipelines, Model Monitoring, and Vector Search.

• Familiarity with knowledge graphs, grounding models, fact checking models.

• Building SDKs or developer frameworks adopted across multiple teams.

• On prem or hybrid AI deployment experience.

AI Ethics Specialist, Standards, Measurement & Governance | Just Horizons Alliance

Join us to define the standards that hold AI systems accountable.

The situation

Just Horizons Alliance is an 18-year-old applied research lab focused on ethics and technology. Our current focus is the AI Ethics Index, a measurement framework for evaluating AI systems on ethics, safety, and societal impact.

We currently have a first version of the framework that is validated and in use. Now we're investing in the next phase: sharper indicator definitions, stronger construct validity, governance processes that hold up to external scrutiny, and measurements that work across domains from education to healthcare to finance.

This is the first dedicated hire to drive the standards and governance layer end-to-end.

What you'll actually do

Months 1–3: Learn the system

Work through the existing L4 indicator library with Sophia. Understand where definitions need tightening, which constructs require the most interpretation, and how the evaluation engine turns indicators into measurements. Start giving developers working definitions they can implement.

Months 4–6: Build the governance infrastructure

Lead the development of a versioning and change control process for the Index. Define disclosure policies. Formalize internal ethical oversight processes. Collaborate with domain experts in education, healthcare, and finance to validate indicators across contexts.

Months 7–12: Drive the standard

Be the person who gives definitive answers on construct interpretation. Manage the L4 indicator framework as a living, governed document. Represent the methodological rigor of the Index in external conversations with regulators, academics, and the organizations being evaluated.

Why this role is hard

You're working at the frontier of a field that does not have settled answers. There is no ISO standard for AI ethics measurement. The frameworks you're building will be contested by academics, challenged by the AI companies being evaluated, and scrutinized by regulators. You need to make defensible decisions under genuine uncertainty, document your reasoning clearly, and communicate it to people who will disagree.

The daily work involves uncomfortable specifics. What does \"sexually explicit content\" mean when an LLM is used in a youth education context—a tutoring app, a storytelling tool, an educational assistant? Where exactly is the boundary? You have to define it in terms a developer can implement and an auditor can verify.

The pace is weeks, not semesters.

You're probably the right person if

You've taken an abstract ethical principle and turned it into something a developer could build or a compliance team could audit

You understand NIST AI RMF or the EU AI Act at a working level — not awareness, but enough to argue about the details

You have external credibility in the field: publications, recognised work, advisory roles, or a title that carries weight

KYC, compliance, or governance experience is part of your background alongside ethics expertise

You work at the pace of decisions, not the pace of studies

You can hold a substantive conversation with a software developer about API behaviour and with a philosopher about construct validity — on the same day

You can read an inter-rater reliability methodology and understand what it means for your indicator definitions

You're probably not the right fit if

Your background is purely academic ethics — you've written and published but never operationalized anything

You need months of research before committing to a position on a specific indicator definition

You're primarily a communicator or writer about AI ethics rather than a practitioner of governance

You're based on the West Coast US or don't work in East Coast US or Western Europe time zones

You see \"working with developers\" as someone else's job

Hard Skills

These are the domain and technical capabilities you need going in — or need to be able to build up fast. You don't need to be an engineer. But you do need to learn quickly, including using AI tools to close knowledge gaps on the fly.

• NIST AI RMF and EU AI Act — working-level knowledge, not awareness. Enough to argue about the details and identify where a specific AI system fails to comply
• Construct operationalization — demonstrated experience translating an abstract ethical principle into a bounded, testable indicator that someone else can use
• Governance documentation — writing versioning policies, change control frameworks, and disclosure protocols that other people actually use day to day
• AI evaluation methodology — familiarity with how AI systems are benchmarked, where measurement goes wrong, and what validity means in a scientific context
• Basic technical literacy — able to read API documentation, understand what a model endpoint does.
• Statistical reliability concepts — inter-rater reliability, aggregation methods, and what it means for a measurement to be valid versus merely reliable
• KYC or compliance frameworks — experience building governance processes that have real enforcement teeth, not just principles documents that no one is held to

What you get

The role: Work directly with Sophia Zitman (AIEI Team Lead) as the person who owns the methodological integrity of the AI Ethics Index. Direct daily collaboration with the development team.

The comp: $110,000

The team: Small, split between ethicists and engineers. Interview panel: Janet Kang and Sophia Zitman.

The environment: Boston-based non-profit (501(c)(3)). East Coast US or Western Europe time zones strongly preferred. Deliberate, rigorous culture.

The upside: You'll have built the governance foundation of what may become the globally referenced standard for AI ethics measurement. That is a genuinely consequential body of work.